The Geometry of Navigation Problems
arXiv:2201.04426 · doi:10.1109/TAC.2022.3144328
Abstract
While many works exploiting an existing Lie group structure have been proposed for state estimation, in particular the Invariant Extended Kalman Filter (IEKF), few papers address the construction of a group structure that allows casting a given system into the framework of invariant filtering. In this paper we introduce a large class of systems encompassing most problems involving a navigating vehicle encountered in practice. For those systems we introduce a novel methodology that systematically provides a group structure for the state space, including vectors of the body frame such as biases. We use it to derive observers having properties akin to those of linear observers or filters. The proposed unifying and versatile framework encompasses all systems where IEKF has proved successful, improves state-of-the art "imperfect" IEKF for inertial navigation with sensor biases, and allows addressing novel examples, like GNSS antenna lever arm estimation.
arXiv commentPublished in IEEE Transactions on Automatic Control, 21 January 2022
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Cited by in corpus (5)
- The Geometry of Navigation Problems
- Know What You Don't Know: Consistency in Sliding Window Filtering with Unobservable States Applied to Visual-Inertial SLAM (Extended Version)
- Invariant Kalman Filtering with Noise-Free Pseudo-Measurements
- On the Existence of Linear Observed Systems on Manifolds with Connection
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